Estimating Macroplastic Mass Transport from Urban Runoff in a Data-Scarce Watershed: A Case Study from Cordoba, Argentina
Urban growth has intensified the generation of solid waste, particularly in densely populated and vulnerable neighborhoods, leading to environmental degradation and public health risks. This study presents a multidisciplinary methodology to estimate the mass of macroplastic litter mobilized from urban surfaces into nearby watercourses during storm events. Focusing on the Villa Páez neighborhood in Cordoba, Argentina—a data-scarce and flood-prone urban basin—the approach integrates socio-environmental surveys, field observations, Google Street View analysis, and hydrologic modeling using EPA SWMM 5.2. Macroplastic accumulation on streets was estimated based on observed waste density, and its transport under varying garbage collection intervals and rainfall intensities was simulated using a conceptual pollutant model. Results indicate that plastic mobilization increases substantially with storm intensity and accumulation duration, with the majority of macroplastic mass transported during high-return-period rainfall events. The study highlights the need for frequent waste collection, improved monitoring in vulnerable urban areas, and scenario-based modeling tools to support more effective waste and stormwater management.
Authors
- Susana Vanoni (ORCID: https://orcid.org/0000-0002-0417-824X)
- María Lábaque
- Ingrid Strusberg (ORCID: https://orcid.org/0000-0003-4469-0560)
- Sebastián López (ORCID: https://orcid.org/0000-0001-7868-181X)
- Teresa Reyna (ORCID: https://orcid.org/0000-0003-2114-0806)
- Carlos M. García (ORCID: https://orcid.org/0000-0002-4091-6756)
- María Fernanda Funes
Institutions
- Universidad Nacional de Córdoba (AR)
- Centro Científico Tecnológico - San Juan (AR)
Publication Details
- Journal
- Sustainability
- Published
- 2025-07-05
- DOI
- https://doi.org/10.3390/su17136177
- Citations
- 1
- Primary Topic
- Microplastics and Plastic Pollution
- Type
- article
- Field-Weighted Citation Impact
- 0.50